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What software environments on NeSI are optimised for Machine Learning and data science?

When using NeSI's HPC platform, you can bring your own code to install or you can access our extensive software library which is already built and compiled, ready for you to use.

Examples of software environments on NeSI optimised for data science include:

  • R and Python users can get right into using and exploring the several built-in packages or create custom code.

  • Jupyter on NeSI is particularly well suited to artificial intelligence and machine learning workloads. R Studio and/or Conda can be accessed via Jupyter.

  • Commonly used data science environments and libraries such as Keras, LambdaStack, Tensorflow and Conda are available to create comprehensive workflows.

For more information about available software and applications, you can browse our catalogue.

As pictured in the screenshot below, you can type keywords into the catalogue's search field to browse by a specific software name or using more broad terms such as "machine learning".


For more information on NeSI's model and approach to application support, refer to our policy for the management of scientific application software.

If you need help installing your software or would like to discuss your software needs with us, Contact our Support Team.